The philosophical division centers on whether models should reflect deterministic relationships, as seen in Newtonian physics, or rely on probabilistic simplifications like statistical mechanics and Claude Shannon's Markov chains. Decades after Shannon applied probabilistic frameworks requiring massive parameter sets to communication, researchers continue using large-scale corpus evaluations to test traditional linguistic rules. For example, a trillion-word dataset shows that the standard spelling rule concerning the sequence of the letters I and E fails under strict frequency testing.
Key points
Purely predictive statistical modeling is seen by critics as failing to address the true…: Purely predictive statistical modeling is seen by critics as failing to address the true meaning beneath observable phenomena.
Physics demonstrates that models can successfully balance deterministic equations with st…: Physics demonstrates that models can successfully balance deterministic equations with statistical inference or simplify complex interactions through probability.
Empirical evaluations using large text corpora can invalidate long-standing discrete educ…: Empirical evaluations using large text corpora can invalidate long-standing discrete educational heuristics through direct statistical counts.
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derided researchers in machine learning who use purely statistical methods to produce behavior that mimics something in the world, but who don't try to understand the meaning of that behavior.The transcript is now available, so let's quote Chomsky himself:
It's true there's been a lot of work on trying to apply statistical models to various linguistic problems. I think there have been some successes, but a lot of failures. There is a notion of success ... which I think is novel in the history of science. It interprets success as approximating unanalyzed data.
Chomsky's remarks were in response to Steven Pinker's question about the success of probabilistic models trained with statistical methods. This essay is a response to Pinker and Chomsky, and will address these questions:
For example, a decade before Chomsky, Claude Shannon proposed probabilistic models of communication based on Markov chains of words. If you have a vocabulary of 100,000 words and a second-order Markov model in which the probability of a word depends on the previous two words, then you need a quadrillion (1015) probability values to…
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